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Title: VOVO : VCR-oriented video-on-demand in large-scale peer-to-peer Networks
Authors: He, Yuan
Liu, Yunhao
Keywords: Peer-to-peer
Issue Date: Apr-2009
Citation: IEEE Transactions on Parallel and Distributed Systems, v. 20, no. 4, 2009, p. 528-539. (pre-published version)
Abstract: Most P2P Video-on-Demand (VOD) schemes focus more on mending service architectures and optimizing overlays but do not carefully consider the user behavior and the benefit of prefetching strategies. As a result, they cannot better support VCR-oriented services in terms of substantive asynchronous clients or free VCR controls for P2P VODs. To address this issue, we propose VOVO, a VCR-oriented VOD for large-scale P2P networks. By mining associations inside each video, the segments requested in VCR interactivities are predicted based on the information collected through gossips. Together with a hybrid caching strategy, a collaborative prefetching scheme is designed to optimize resource distribution among neighboring peers. We evaluate VOVO through extensive experiments. Results show that VOVO is scalable and effective, providing short start-up latencies and good performance in VCR interactivities.
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